These solutions focus on identifying undocumented endpoints, detecting broken object-level authorization, and monitoring traffic for anomalous data exfiltration patterns. They serve to bridge the gap between development speed and robust infrastructure hardening by automating constant discovery and threat appraisal. When evaluating these options, prioritize the depth of their integration with your existing gateway and their ability to provide actionable context rather than overwhelming noise.

Cryptographic identity for autonomous AI agents

Trust Layer for Autonomous AI

Build and Activate AI agents from a single modular dashboard

Passport for AI Agents

Secure Identity and Authorization for AI Agents

Your AI security copilot for HTTP requests.

Identity and trust for AI agents — verify, revoke, enforce

Guard your AI from prompt attacks, harmful content, and PII

Real time security for AI and LLM applications

The firewall for AI prompts. Drop-in security for LLM apps.

The production layer for MCP servers — OAuth, limits, evals

AI-powered real-time content moderation & censorship shield

Secure The Unknown

Block Unsafe AI Agent Actions Before They Execute

AI wallet that lets web apps use your models, not your keys

Run 60+ attack prompts to secure LLM APIs before release